Chang-Han Rhee

Chang-Han Rhee is an Assistant Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University's McCormick School of Engineering. His research focuses on applied and theoretical probability, stochastic simulation, experimental design, and machine learning theory. He holds a Ph.D. and M.S. in Computational and Mathematical Engineering from Stanford University (2012–2017) and a B.Sc. in Mathematics and Computer Science from Seoul National University (2008–2012).

His work emphasizes rare-event simulation, large deviations theory, and heavy-tailed stochastic processes, with applications in queueing systems, financial risk analysis, and optimization. Notable contributions include developing efficient simulation techniques for systems with catastrophic events and heavy-tailed dynamics. His research bridges theoretical foundations with practical computational methods, addressing challenges in stochastic modeling and heavy-tailed phenomena.

Rhee has received the NSF CAREER Award (2022) for his work on catastrophic rare events and heavy-tailed systems. His publications span high-impact journals like Annals of Applied Probability and Mathematics of Operations Research, focusing on topics such as large deviations, Markov processes, and stochastic fluid networks. His recent work explores metastability in dynamical systems and optimization methods to mitigate sharp minima in machine learning algorithms.